2015 Informs Annual Meeting

TC07

INFORMS Philadelphia – 2015

4 - Speculative Oil Anna Kruglova, Research Affiliate, MIT Center for Finance and Policy, 30 Memorial Drive, Cambridge, MA, 02142, United States of America, Kruglova@mit.edu, Andrei Kirilenko The long-standing framework predicated on a premise that producers are the main drivers of energy prices, the so-called “hedging pressure” theory, has been shown to be less consistent with the empirical regularities present in the oil prices. We hypothesize that with the influx of financial investors, the last needed barrel is traded not between a hedger and a speculator, but between two speculators: a commodity trader and/or a bank. We use granular information on shipments of seaborne crude oil into the US during 2008-2012 to examine the industry structure and determine who holds the crude oil that supports the determination of prices in financial markets. TC07 07-Room 307, Marriott Systemic Risk: Methods and Models Cluster: Risk Management Invited Session Chair: David Brown, Duke University Fuqua School of Business, 1 Towerview Rd, Durham, NC, United States of America, dbbrown@duke.edu 1 - Time-varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads Dong Hwan Oh, Economist, Federal Reserve Board, 20th Street and Constitution Avenue N.W., Washington, DC, 20551, United States of America, donghwan.oh@frb.gov, Andrew Patton This paper proposes a new class of copula-based dynamic models for high- dimensional conditional distributions, facilitating the estimation of a wide variety of measures of systemic risk. We use the proposed new models to study a collection of daily credit default swap spreads on 100 U.S. firms. We find that while the probability of distress for individual firms has reduced since the financial crisis of 2008-09, the joint probability of distress is substantially higher now than in the pre-crisis. 2 - An Optimization View of Financial Systemic Risk Modeling Nan Chen, Prof, Chinese University of Hong Kong, 709A William Mong Engineering Building, Hong Kong, Hong Kong - PRC, nchen@se.cuhk.edu.hk, Xin Liu, David D. Yao We develop an optimization-based formulation on financial systemic risk. A partition algorithm is constructed to solve the problem. The sensitivity analysis helps us identify two multipliers to characterize the amplification effects caused by liability networks and market liquidity. The effects of policy intervention are also discussed in the paper. 3 - Optimal Capital Requirements in Interbank Networks with Fire Sales Externality Jongsoo Hong, Duke University, 1 Towerview Rd, Durham, NC, 27707, United States of America, jongsoo.hong@duke.edu, David Brown We consider an interbank network with fire sales externality and study the problem of optimally trading off between capital reserves and systemic risk. We find that the optimal capital requirements is a solution to a stochastic linear programming without fire sales externality and a stochastic mixed integer programming with fire sales externality. We offer an iterative algorithm that converges to the optimal. We demonstrate the methods on an example using data from a central bank. TC08 08-Room 308, Marriott Different Facets of Innovation: Product, Technology and Business Models Cluster: Business Model Innovation Invited Session Chair: Serguei Netessine, Professor, INSEAD, 1 Ayer Rajah Avenue, Singapore, 138676, Singapore, Serguei.Netessine@insead.edu 1 - Identifying and Analyzing Styles in Design Patents Tian Chan, INSEAD, TianHeong.CHAN@insead.edu, Jurgen Mihm, Manuel Sosa We introduce an approach to identify styles (categories of product designs similar in form) among 400,000 US design patents. We combine state-of-the-art clustering techniques with experimental validation to create, for the first time, a dataset of styles. Building on this platform, we find that i) the level of turbulence (unpredictability of changes) in styles follows a U-shaped pattern to the level of turbulence in functionality, and ii) styles turbulence is increasing over time.

2 - Free Riding in Team Projects: The Role of the Leadership Style Morvarid Rahmani, Assistant Professor, Georgia Tech, morvarid.rahmani@scheller.gatech.edu, Uday Karmarkar, Guillaume Roels In order to remain innovative in today’s global market, firms are increasingly organizing work around teams. In this paper, we investigate the role of the leadership style (autocratic or democratic) on free-riding in teams and characterize which leadership style is the most efficient depending on the project characteristics. 3 - Different Approaches to Crowdfunding: Kickstarter vs. Indiegogo Simone Marinesi, Wharton, 562 Jon M. Huntsman Hall, 3730 Walnut St, Philadelphia, PA, 19104, United States of America, marinesi@wharton.upenn.edu, Karan Girotra We compare the different modes of interaction between backers and creators offered in the two most famous crowdfunding platforms, and provide prescriptions on their implementation, taking the view of project creators. 4 - Are Good Idea Generators also Good at Evaluating Ideas Otso Massala, INSEAD, 1 Ayer Rajah Avenue, Singapore, Singapore, Otso.MASSALA@insead.edu Using data collected from a series of innovation tournaments we relate different business opportunity generation skills with evaluation skills. We find that prolific generators are worse evaluators while generators that produce high quality ideas tend to also be good at evaluating. We provide implications for design of innovation tournaments and innovative organizations. TC09 09-Room 309, Marriott Crowd Innovation Sponsor: Technology, Innovation Management & Entrepreneurship Sponsored Session Chair: Mohamed Mostagir, Assistant Professor, University of Michigan Ross School of Business, 701 Tappan Ave, R5316, Ann Arbor, MI, 48109, United States of America, mosta@umich.edu 1 - Time-Based Crowdsourcing Contests Ersin Korpeoglu, Carnegie Mellon University, 5000 Forbes Avenue, Pittsbugh, PA, United States of America, ekorpeog@andrew.cmu.edu, Laurence Ales, Soo-Haeng Cho We study a crowdsourcing contest wherein a seeker solicits a population of agents to solve a problem. Each agent’s stochastic solution time depends on her effort and expertise. We show that it is optimal for the seeker to screen and compensate only the highest-expertise agents when their solution times are less uncertain, but a larger group of agents when they are highly uncertain. An agent’s optimal compensation is based on her solution time and whether the seeker can observe agents’ efforts. 2 - Payoffs in Contests Kevin Boudreau,Harvard University and London Business School, Harvard Business School, Cambridge MA, United States of America, kboudreau@hbs.edu, Karim Lakhani, Nichale Menietti Many tournament outcomes possess signaling value. In this article, the results of a field experiment on signaling incentives are presented. Using a structural model, we obtain estimates of the value of nominal prizes, as well as extra value associated with the contest. Signaling and cash values exhibit large interaction effects. In all conditions, the perceived value of the prizes differs from the nominal value. Competitors tend to undervalue small prizes and overvalue large prizes. 3 - Achieving Efficiency in Dynamic Contribution Games George Georgiadis, Assistant Professor, Northwestern University, 2001 Sheridan Rd, Evanston, IL, 60208, United States of America, g-georgiadis@kellogg.northwestern.edu, Jaksa Cvitanic We analyze a dynamic contribution game, in which a group of agents exert costly effort over time to make progress on a project that generates a lump-sum payoff once the cumulative effort reaches a pre-specified threshold. We characterize a budget balanced mechanism which overcomes the free-rider problem, and at every moment, induces each agent to exert the first-best effort level in a Markov Perfect Equilibrium. Applications include early-stage entrepreneurial ventures and joint R&D ventures.

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